Known methods of motion capture may include camera-type systems, wherein reflective markers attached to the body are observed by a number of cameras from which the 3D position can be reconstructed using triangulation of each camera 2D image. On the other hand, magnetic-type trackers measure the field as emitted by a source placed near the subject from which position, orientation, acceleration, and/or velocity of the sensor with respect to the source can be calculated. Other systems include the use of inertial measurement units (IMUs) or goniometers disposed on a body that capture position, orientation, acceleration, and/or velocity data of the body in a three-dimensional space. However, such systems commonly suffer from drift and noise errors that affect the accuracy of the motion data being processed. While some methods implement the use of predetermined kinetic calculations and/or predetermined data generated by contact of the body with the external world, such methods of updating the motion data still suffer from inaccuracies due to the fact that they are relying on limitations that are not generated by the motion sensors themselves, or are not generated in real time. Accordingly, there remains a need to develop motion sensor methods and systems that have the ability to more accurately capture the three-dimensional position, orientation, acceleration, and/or velocity of the object.